Reliable by Design

Software engineers have been shipping AI features for years. Too many of them are held together by prompt strings.

The problem is not the models. The models are extraordinary. The problem is the layer between the model and production: the code that calls it, validates its output, handles its failures, controls its cost, and keeps it from doing something catastrophic on a Saturday night.

That layer is where this book lives.

Reliable by Design is a production engineering curriculum for software engineers who are done with demos. It covers the full stack of concerns that appear the moment a model hits production: type-safe output handling, retrieval architecture, eval pipelines, agent control flow, security, observability, and cost governance.

The central argument is simple: a model is a probabilistic kernel. Your software system must be the deterministic shell around it. That shell is where reliability lives, and building it well is an engineering problem, not a research problem.

This is not a book about prompting. It is not a book about which model to use. It is a book about the craft of building AI systems that survive contact with real users, real budgets, and real incidents.